This blog examines past, current, and best practices, techniques, and lessons learned of various business intelligence implementations.

GIS

May 10, 2008

Today, many companies are turning to a variety of data visualization capabilities to significantly enhance their business intelligence applications.While there are many advanced visualization techniques to choose from, one of the most valuable – the incorporation of geographic information systems into reporting and analysis environments – has been widely underutilized in today’s business world, as many industry experts will agree.

Geographic information systems make it possible for companies to access, present, and analyze spatially-oriented or demographic information from a variety of enterprise data sources.In a typical scenario, a user will query data from a database or data warehouse, and the results will be presented on a map for viewing.Shapes, color-coding, and other graphical styling can be used to segment and differentiate various information elements.

What makes this approach so compelling?Because it empowers users to fully understand business intelligence data as it correlates to specific locations.For example:

A retailer can identify “clusters” of potential customers, to best determine where new stores should be opened.

Law enforcement agencies can better analyze crime statistics by area, to determine where additional officers may be needed.

Companies of all types can more accurately assess market penetration by region.

Logistics service providers can more effectively plan routes by seeing all required deliveries in a given area.

It would be quite challenging to properly interpret these types of information using traditional row-and-column or spreadsheet reports, and vital patterns and trends may be overlooked.

While there are many different methods of applying GIS in business intelligence environments, some of the best and most effective ways to present spatially-oriented enterprise data is through:

Thematic mapping, which collects information associated with pre-defined geo-coded data points (i.e. the addresses of branch offices), aggregates them to the appropriate geographic regions, and displays them on a map.

Customer dot mapping, which presents client locations as dots spread across a defined area map.More advanced customer dot mapping can show customer locations with respect to store locations.

Trade area analysis, which displays the locations of members of a target audience, and uses various graphic techniques to indicate specific traits and behaviors.For example, a grocery retailer can view potential customers, and color code them based on annual household income or use different shapes to indicate number of family members.

Spacial interaction modeling, which uses trends in historical demographic data to forecast future events in a specific location.For example, based on the average length of time each family lives in a home, and the number of houses that have been sold in a given region over a certain time period, real estate firms can predict how many homes – and which ones – are likely to be put up for sale over the next several months.

The ways in which GIS can be used to address issues, identify opportunities, and understand marketplace trends is virtually endless.By integrating advanced mapping capabilities into their business intelligence environments, organizations can better visualize and interpret their spatial information, and gain insight into the vital relationships that exist among it.